In addition to the uncertainty for motion/relocalization, estimating the uncertainty for scene understanding also contributes to SLAM systems. This uncertainty offers a belief metric in to what extent the environmental perception and scene structure should be trusted. For example, in the semantic segmentation and depth estimation tasks, uncertainty estimation provides per-pixel uncertainties for the DNN predictions [1]}, [2]}, [3]}, [4]}.
Further more, scene uncertainty is applicable to building hybrid SLAM systems. For example, photometric uncertainty can be learned to capture the variance of intensity on each image pixel, and hence enhances the robustness of SLAM system to observation noise [5]}.
